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Overview

Runtime materialization helps to bring your SDF model from a development environment to live tables in production. It works against remote warehouses and the local SDF database alike:
  • Materialize models as views, tables, incremental tables, transient tables, temporary views, recursive tables, and more.
  • Debug your models faster and at no cost, since static analysis checks errors before running them.
  • Run tables with Jinja, SQL Variables, or other relevant metadata without manually converting them to plain SQL.
Materialization is executed as part of sdf run.

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Materialization Prerequisites

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Prerequisites

In order to materialize tables in your data warehouse, you will need to have the following:
  1. A Snowflake or Redshift warehouse to materialize tables remotely.
  2. Valid credentials with write access to materialize tables in your warehouse.
  3. A configured integration in your workspace.sdf.yml file.
As such, we recommend starting with our integrations documentation before proceeding with materialization.

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Materialization Guides

Below are a list of follow-along guides to help you get started with materialization in SDF. Since materialization differs between warehouses, each guide walks you through a specific materialization type in a specific warehouse.
Materialization TypeSnowflakeRedshiftBigQuery
ViewLinkComing soon…Coming soon…
TableLinkComing soon…Coming soon…
IncrementalLinkComing soon…Coming soon…
SDF supports a wide variety of materialization options. See the materialization config to view them all.